class_docstr: Add random camera radial distortion.
  
  .. image:: _static/img/RandomFisheye.png
  
  Args:
      center_x: Ranges to sample respect to x-coordinate center with shape (2,).
      center_y: Ranges to sample respect to y-coordinate center with shape (2,).
      gamma: Ranges to sample for the gamma values respect to optical center with shape (2,).
      same_on_batch: apply the same transformation across the batch.
      p: probability of applying the transformation.
      keepdim: whether to keep the output shape the same as input (True) or broadcast it
               to the batch form (False).
  
  Examples:
      >>> import torch
      >>> img = torch.ones(1, 1, 2, 2)
      >>> center_x = torch.tensor([-.3, .3])
      >>> center_y = torch.tensor([-.3, .3])
      >>> gamma = torch.tensor([.9, 1.])
      >>> out = RandomFisheye(center_x, center_y, gamma)(img)
      >>> out.shape
      torch.Size([1, 1, 2, 2])
  
  To apply the exact augmenation again, you may take the advantage of the previous parameter state:
      >>> input = torch.randn(1, 3, 32, 32)
      >>> aug = RandomFisheye(center_x, center_y, gamma, p=1.)
      >>> (aug(input) == aug(input, params=aug._params)).all()
      tensor(True)
code: def __init__(
      self,
      center_x: Tensor,
      center_y: Tensor,
      gamma: Tensor,
      same_on_batch: bool = False,
      p: float = 0.5,
      keepdim: bool = False,
  ) -> None:
      super().__init__(
          p=p, same_on_batch=same_on_batch, p_batch=1.0, keepdim=keepdim
      )
      self._check_tensor(center_x)
      self._check_tensor(center_y)
      self._check_tensor(gamma)
      self._param_generator = rg.PlainUniformGenerator(
          (center_x[:, None], "center_x", None, None),
          (center_y[:, None], "center_y", None, None),
          (gamma[:, None], "gamma", None, None),
      )
  
file_path: kornia/kornia/augmentation/_2d/geometric/fisheye.py
imports: from typing import Any, Dict, Optional
  from kornia.augmentation import random_generator
  from kornia.augmentation._2d.base import AugmentationBase2D
  from kornia.core import Tensor
  from kornia.geometry.transform import remap
  from kornia.utils import create_meshgrid
label_desc: Use image node_id 1 to create a new RandomFisheye object from inherited base classes: AugmentationBase2D with example: obj = RandomFisheye(center_x, center_y, gamma, same_on_batch, p, keepdim)